Differential analysis between somatic mutation and germline variation profiles reveals cancer-related genes

Pawel F Przytycki,Mona Singh

doi:10.1186/s13073-017-0465-6

Abstract

A major aim of cancer genomics is to pinpoint which somatically mutated genes are involved in tumor initiation and progression. We introduce a new framework for uncovering cancer genes, differential mutation analysis, which compares the mutational profiles of genes across cancer genomes with their natural germline variation across healthy individuals. We present DiffMut, a fast and simple approach for differential mutational analysis, and demonstrate that it is more effective in discovering cancer genes than considerably more sophisticated approaches. We conclude that germline variation across healthy human genomes provides a powerful means for characterizing somatic mutation frequency and identifying cancer driver genes. DiffMut is available at https://github.com/Singh-Lab/Differential-Mutation-Analysis.

Highlights

Large-scale cancer genome sequencing consortia, such as The Cancer Genome Atlas (TCGA) [1] and ICGC [2], have provided a huge influx of somatic mutation data across large cohorts of patients
Identifying cancer driver genes by differential mutation analysis We applied our method to all 24 cancer types sequenced in TCGA using all non-silent mutations (Additional file 1: Section A)
We evaluated our method by examining whether the Cancer Gene Census (CGC) list of known cancer driver genes, as curated by COSMIC [26], is enriched among genes with high unidirectional Earth Mover’s Difference (uEMD) scores

Summary

Introduction

Large-scale cancer genome sequencing consortia, such as TCGA [1] and ICGC [2], have provided a huge influx of somatic mutation data across large cohorts of patients. Understanding how these observed genetic alterations give rise to specific cancer phenotypes represents a major aim of cancer genomics [3]. Initial analyses of cancer genomes have revealed that numerous somatic mutations are usually observed within each individual and yet only a subset of them is thought to play a role in tumor initiation or progression [4]. A high background mutation rate in a gene is indicative of that gene’s propensity to accumulate mutations, thereby suggesting that mutations within it are more likely to be neutral [11]

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